Radar fault root cause judgment method and device based on graph distance search

Abstract

The embodiment of the invention provides a radar fault root cause judgment method and device based on graph distance search, and is applied to the technical field of meteorological radar fault monitoring. The method comprises the following steps: acquiring a key alarm code sequence of a fault period; determining a causal alarm code sequence corresponding to the key alarm code sequence through a graph distance search algorithm based on a preset alarm code path graph; and calculating the alarm code proportion of each fault type in the causal alarm code sequence to obtain the membership of each fault type, and taking the fault type with the maximum membership as the fault root cause type of the radar fault. In this way, the key causal alarm code sequence related to the SA radar fault can be rapidly and accurately extracted based on the preset alarm code path diagram, and accurate judgment of the root cause of the SA radar fault is achieved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing, in particular to the field of meteorological radar fault monitoring technology, and specifically to a method and device for determining the root cause of radar faults based on graph distance search. Background Art

[0002] The CINRAD / SA new generation weather radar is the main model of current weather radars, and its fault identification and determination have always been technical challenges faced by radar operation and maintenance. The radar data acquisition subsystem (Radar Data Acquisition, RDA) has an alarm information output function, and corresponding RDA alarm information will be generated when an SA radar fails.

[0003] However, when a certain type of radar fault occurs, it will cause the loss of function of other components, and often trigger alarm codes of other fault types, resulting in the alternating appearance of alarm codes of various fault modes. Based on this, there is a high-difficulty technical challenge in how to use the key alarm code information to diagnose the true root cause of SA radar faults. Summary of the Invention

[0004] The present disclosure provides a method and device for determining the root cause of radar faults based on graph distance search.

[0005] According to a first aspect of the present disclosure, there is provided a method for determining the root cause of radar faults based on graph distance search. The method includes:

[0006] Obtaining a key alarm code sequence during a fault period;

[0007] Based on a preset alarm code path graph, determining a causal alarm code sequence corresponding to the key alarm code sequence through a graph distance search algorithm;

[0008] Calculating the proportion of alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type, and taking the fault type with the largest membership degree as the root cause type of the radar fault.

[0009] As described above in the aspect and any possible implementation manner, a further implementation manner is provided, where the obtaining of the key alarm code sequence during the fault period includes:

[0010] Obtaining all alarm codes during the fault period;

[0011] Based on the matching relationship between a preset fault mode and key alarm codes, extracting a key alarm code sequence from all the alarm codes.

[0012] As described above in the aspect and any possible implementation manner, a further implementation manner is provided, where the construction of the preset alarm code path graph includes:

[0013] Construct a preset alarm code path graph with alarm codes as nodes and the causal probability between alarm codes as edge weights;

[0014] Among them, the edge direction of the preset alarm code path graph is from the node that appears earlier to the node that appears later, and the number of subsequent alarm codes that an alarm code can affect does not exceed a preset number; the alarm code and the causal probability are calibrated according to historical fault records.

[0015] For the above aspects and any possible implementation manners, a further implementation manner is provided. Based on the preset alarm code path graph, through the graph distance search algorithm, determining the causal alarm code sequence corresponding to the key alarm code sequence includes:

[0016] Based on the preset alarm code path graph, through the graph distance search algorithm, determine that the path with the maximum causal probability from the earliest key alarm code to the end key alarm code in the key alarm code sequence is the causal alarm code sequence corresponding to the key alarm code sequence.

[0017] For the above aspects and any possible implementation manners, a further implementation manner is provided. Calculating the proportion of alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type includes:

[0018] Based on the matching relationship between the preset fault mode and the key alarm code, calculate the proportion of alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type.

[0019] For the above aspects and any possible implementation manners, a further implementation manner is provided. The membership degree of each fault type is the ratio of the frequency of the alarm codes belonging to each fault type that appear in the causal alarm code sequence to the total frequency of the alarm codes in the causal alarm code sequence.

[0020] For the above aspects and any possible implementation manners, a further implementation manner is provided. The graph distance search algorithm is the A-Star search algorithm.

[0021] According to the second aspect of the present disclosure, a radar fault root cause determination device based on graph distance search is provided. The device includes:

[0022] An acquisition module, configured to acquire a key alarm code sequence during a fault period;

[0023] A determination module, configured to determine the causal alarm code sequence corresponding to the key alarm code sequence based on a preset alarm code path graph through a graph distance search algorithm;

[0024] A calculation module, configured to calculate the proportion of alarm codes of each fault type in the causal alarm code sequence, obtain the membership degree of each fault type, and use the fault type with the largest membership degree as the root cause type of the radar fault.

[0025] According to a third aspect of the present disclosure, an electronic device is provided. The electronic device includes: a memory and a processor, where a computer program is stored on the memory, and when the processor executes the program, the method described above is implemented.

[0026] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method described above is implemented.

[0027] A method and device for determining the root cause of radar faults based on graph distance search provided by an embodiment of the present application can obtain a key alarm code sequence during a fault period; then, based on a preset alarm code path graph, use a graph distance search algorithm to determine a causal alarm code sequence corresponding to the key alarm code sequence; then calculate the proportion of alarm codes of each fault type in the causal alarm code sequence, obtain the membership degree of each fault type, and use the fault type with the largest membership degree as the root cause type of the radar fault; based on this, it is possible to quickly and accurately extract a key causal alarm code sequence related to SA radar faults based on the preset alarm code path graph and achieve an accurate determination of the root cause of SA radar faults.

[0028] It should be understood that the content described in the summary of the invention section is not intended to limit the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] With reference to the accompanying drawings and the following detailed description, the above and other features, advantages, and aspects of the embodiments of the present disclosure will become more apparent. The drawings are used to better understand the solution and do not constitute a limitation to the present disclosure. In the drawings, the same or similar reference numerals represent the same or similar elements, where:

[0030] Figure 1 shows a flowchart of a method for determining the root cause of radar faults based on graph distance search according to an embodiment of the present disclosure;

[0031] Figure 2 shows a schematic diagram of a preset alarm code path graph according to an embodiment of the present disclosure;

[0032] Figure 3 shows a block diagram of a device for determining the root cause of radar faults based on graph distance search according to an embodiment of the present disclosure;

[0033] Figure 4A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. Detailed implementation manners

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are some but not all of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present disclosure without creative efforts shall fall within the protection scope of the present disclosure.

[0035] In addition, the term "and / or" in this article is merely used to describe an associated relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, both A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0036] In the present disclosure, the key causal alarm code sequence related to the SA radar fault can be quickly and accurately extracted based on the preset alarm code path diagram, and the accurate determination of the root cause of the SA radar fault can be realized.

[0037] Figure 1 A flowchart of a radar fault root cause determination method 100 based on graph distance search according to an embodiment of the present disclosure is shown.

[0038] At block 110, obtain the key alarm code sequence during the fault period.

[0039] In some embodiments, the key alarm code sequence during the fault period can be extracted by a preset extraction rule. The preset extraction rule can be set according to the actual needs of the user.

[0040] For example, for the alarm codes during a fault period, the extraction rule includes:

[0041] Extract all the alarm codes within the time interval T before the radar shutdown state, where T is the development time of the fault, and the default is 24 hours;

[0042] Extract the alarm code sequence belonging to the key alarm code set {A ij} as the key alarm code sequence.

[0043] Among them, a key alarm code sequence can be as follows:

[0044] A 11 , A 12 , A 22 , A 11 , A 13 , A23 , A 21

[0045] The above - mentioned critical alarm code sequence is the alternating appearance of alarm codes for the first - type fault mode F1 and the second - type fault mode F2, and the same alarm code may appear multiple times, such as A 11 appears twice. Based on this, it is necessary to solve how to determine the true root - cause type of the fault during this fault period, that is, to analyze whether it is an F1 fault or an F2 fault.

[0046] In some embodiments, the obtaining of the critical alarm code sequence for the fault period includes:

[0047] Obtain all alarm codes for the fault period;

[0048] Based on the matching relationship between the preset fault mode and the critical alarm code, extract the critical alarm code sequence from all alarm codes.

[0049] In some embodiments, the matching relationship between the preset fault mode and the critical alarm code can be set according to the actual needs of the user.

[0050] For example, the matching relationship between the fault mode and the critical alarm code can be sorted out according to expert experience, and can also be obtained based on a pre - constructed knowledge base.

[0051] In some embodiments, the matching relationship between the preset fault mode and the critical alarm code may include:

[0052]

[0053] where F i is the i - th type of fault mode, which contains a total of n i kinds of critical alarm codes, A ij is the j - th critical alarm code of the i - th type of fault mode, and there are a total of m types of sorted - out fault modes, then the set of critical alarm codes is {A ij}, i = 1,... m, j = 1,..., n i .

[0054] In block 120, based on the preset alarm - code path graph, through the graph - distance search algorithm, determine the causal alarm - code sequence corresponding to the critical alarm - code sequence.

[0055] In some embodiments, the preset alarm - code path graph can be set according to the actual needs of the user.

[0056] In some embodiments, the construction of the above - mentioned preset alarm - code path graph includes:

[0057] Construct a preset alarm - code path graph with alarm codes as nodes and the causal probability between alarm codes as edge weights;

[0058] Among them, the edge direction of the preset alarm code path diagram is that the node appearing earlier points to the node appearing later, and the number of subsequent alarm codes that one alarm code can affect does not exceed a preset number; the alarm code and the causal probability are calibrated according to historical fault records.

[0059] In some embodiments, the causal probability associated with the alarm code can be calibrated based on all historical fault records, that is, analyze the probability of generating other related alarm codes later when a certain alarm code appears. For alarm code A i The subsequent generation of alarm code A j The probability is:

[0060]

[0061] In some embodiments, the preset number can be set according to the actual needs of the user, for example, 3.

[0062] In some embodiments, an alarm code path diagram can be constructed with alarm codes as nodes and the causal probability between alarm codes as edge weights. The direction of the edge is that the node appearing earlier points to the node appearing later, and the number of subsequent alarm codes that one alarm code can affect does not exceed 3. For example, for the key alarm code A 11 , A 12 , A 22 , A 11 , A 13 , A 23 , A 21 Construct the alarm code path diagram for the key alarm code. The earliest key alarm code is A 11 , and the ending key alarm code is A 21 . The constructed alarm code path diagram is as shown in Figure 2 Shown.

[0063] In some embodiments, based on the preset alarm code path diagram, through the graph distance search algorithm, determining the causal alarm code sequence corresponding to the key alarm code sequence specifically includes:

[0064] Based on the preset alarm code path diagram, through the graph distance search algorithm, determine that the path with the maximum causal probability from the earliest key alarm code to the ending key alarm code in the key alarm code sequence is the causal alarm code sequence corresponding to the key alarm code sequence.

[0065] In some embodiments, after the alarm code path diagram is constructed, a path with the maximum causal probability from the leftmost A 11 node to the rightmost A 21 node can be found, that is, this path is the path with the maximum product of all edge weights from A 11 to A 21 as the causal alarm code sequence corresponding to the key alarm code sequence.

[0066] In some embodiments, the idea of dynamic programming can be adopted, such as determining the critical causal alarm code sequence through a graph distance search algorithm. For example, if ij the causal probability of the path with the largest causal probability at the end point of A is C ij , and its path sequence is R ij ; taking A 22 as an example, R 22 = {A 11 , A 22} or R 22 = {A 11 , A 12 , A 22}; for any alarm code node A ij , the number of precursor alarm code nodes that all point to the A ij node is at most 3, and the 3 parent nodes are denoted as B1, B2, B3. For example, the parent nodes of A 22 are B1 = A 11 , B2 = A 12 ;

[0067] Then, the causal probability of the path with the largest causal probability at the end point of A ij is:

[0068]

[0069] Denote the largest parent node as B, then the path with the largest causal probability at the end point of A ij is R ij = R B + {A ij};

[0070] Initial condition C 11 = 1, R 11 = {A 11};

[0071] The causal path corresponding to the end point is the causal alarm code sequence, denoted as the causal alarm code sequence R = {A'1, A'2,..., A' q}. For example, R 21 = {A 11 , A 12 , A 11 , A 13 , A 21} in the example.

[0072] In block 130, calculate the proportion of the alarm codes of each fault type in the causal alarm code sequence, obtain the membership degree of each fault type, and use the fault type with the largest membership degree as the root cause type of the radar failure.

[0073] In some embodiments, the membership degree of each of the above-mentioned fault types is the ratio of the frequency of the alarm codes belonging to each fault type in the causal alarm code sequence to the total frequency of the alarm codes in the causal alarm code sequence.

[0074] In some embodiments, calculating the proportion of the alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type includes:

[0075] Based on the matching relationship between the preset fault mode and the key alarm codes, calculate the proportion of the alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type.

[0076] In some embodiments, for the causal alarm code sequence R = {A′1, A′2,..., A′ q}, the proportion of the alarm codes of each fault type can be calculated based on the matching relationship between the preset fault mode and the key alarm codes to obtain the membership degree of the fault type.

[0077] For example, for the fault type its fault membership degree is:

[0078]

[0079] That is, the ratio of the frequency of the alarm codes belonging to the fault type F i in the causal alarm code sequence R to the total frequency of the alarm codes in the causal alarm code sequence R is used as the membership degree of the fault type F i .

[0080] In some embodiments, the fault type with the largest membership degree of the fault type can be taken as the root cause type of the fault that occurs in the radar this time.

[0081] According to the embodiments of the present disclosure, the following technical effects are achieved:

[0082] By obtaining the key alarm code sequence during the fault period; then based on the preset alarm code path map, through the graph distance search algorithm, determining the causal alarm code sequence corresponding to the key alarm code sequence; then calculating the proportion of the alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type, and taking the fault type with the largest membership degree as the root cause type of the fault that occurs in the radar; based on this, it is possible to quickly and accurately extract the key causal alarm code sequence related to the SA radar fault based on the preset alarm code path map and achieve the accurate determination of the root cause of the SA radar fault.

[0083] In some embodiments, the above-mentioned graph distance search algorithm is the A-Star search algorithm.

[0084] In some embodiments, the graph distance search algorithm can be the Dijkstra algorithm or the A-Star search algorithm.

[0085] In some embodiments, the A-Star search algorithm is a heuristic search algorithm that combines the characteristics of the best-first search algorithm and the Dijkstra algorithm. It proceeds by considering the distance from the starting point to the current point and the estimated shortest distance from the current point to the target point, and always selects the node with the lowest estimated cost in the graph as the new state. Therefore, the A-Star search algorithm can be selected as the graph distance search algorithm for the above requirements.

[0086] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present disclosure is not limited by the described action sequence, because according to the present disclosure, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to the present disclosure.

[0087] The above is the introduction of the method embodiments. The following further illustrates the solution of the present disclosure through device embodiments.

[0088] Figure 3 The block diagram of a radar fault root cause determination device 300 based on graph distance search according to an embodiment of the present disclosure is shown. As Figure 3 shown, the device 300 includes:

[0089] An acquisition module 310, configured to acquire a sequence of key alarm codes during a fault period;

[0090] A determination module 320, configured to determine a causal alarm code sequence corresponding to the sequence of key alarm codes through a graph distance search algorithm based on a preset alarm code path graph;

[0091] A calculation module 330, configured to calculate the proportion of alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type, and use the fault type with the largest membership degree as the fault root cause type of the radar failure.

[0092] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the described modules can refer to the corresponding process in the foregoing method embodiments, and will not be elaborated herein.

[0093] In the technical solution of the present disclosure, the acquisition, storage, and application of user personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0094] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0095] Figure 4 FIG. 2 shows a block diagram of an exemplary electronic device 400 capable of implementing embodiments of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as, for example, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as, for example, personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0096] The electronic device 400 includes a computing unit 401 that can perform various appropriate actions and processes according to a computer program stored in the ROM 402 or a computer program loaded from the storage unit 408 into the RAM 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. The I / O interface 405 is also connected to the bus 404.

[0097] A plurality of components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a magnetic disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0098] The computing unit 401 can be various general-purpose and / or special-purpose processing components having processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 executes the various methods and processes described above, such as method 100. For example, in some embodiments, method 100 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 408.

[0099] In some embodiments, part or all of the computer program may be loaded and / or installed onto the electronic device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the method 100 by any other suitable means (e.g., by means of firmware).

[0100] Various implementations of the systems and techniques described above in this document may be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor that receives data and instructions from a storage system, at least one input device, and at least one output device, and transmits the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0101] The program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program code may be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0102] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0103] To provide for interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic, speech, or tactile input).

[0104] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0105] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

[0106] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and no limitations are imposed herein.

[0107] The above specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub - combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. A radar fault root cause determination method based on graph distance search, characterized in that Including: Obtain the key alarm code sequence during the fault period; Based on the preset alarm code path graph, determine the causal alarm code sequence corresponding to the key alarm code sequence through the graph distance search algorithm; Calculate the proportion of alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type, and use the fault type with the largest membership degree as the root cause type of the radar fault.

2. The method according to claim 1, characterized in that, The obtaining the key alarm code sequence during the fault period includes: Obtain all alarm codes during the fault period; Based on the matching relationship between the preset fault mode and the key alarm code, extract the key alarm code sequence from all the alarm codes.

3. The method according to claim 1, characterized in that, The construction of the preset alarm code path graph includes: Construct a preset alarm code path graph with alarm codes as nodes and the causal probability between alarm codes as edge weights; Among them, the edge direction of the preset alarm code path graph is from the node that appears earlier to the node that appears later, and the number of subsequent alarm codes that an alarm code can affect does not exceed a preset number; the alarm code and the causal probability are calibrated according to historical fault records.

4. The method according to claim 3, wherein The determining the causal alarm code sequence corresponding to the key alarm code sequence based on the preset alarm code path graph through the graph distance search algorithm includes: Based on the preset alarm code path graph, determine the path with the maximum causal probability from the earliest key alarm code to the end key alarm code in the key alarm code sequence as the causal alarm code sequence corresponding to the key alarm code sequence through the graph distance search algorithm.

5. The method according to claim 2, wherein The calculating the proportion of alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type includes: Based on the matching relationship between the preset fault mode and the key alarm code, calculate the proportion of alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type.

6. The method according to claim 2, wherein The membership degree of each fault type is the ratio of the frequency of the alarm codes that appear in the causal alarm code sequence belonging to each fault type to the total frequency of the alarm codes in the causal alarm code sequence.

7. The method according to any one of claims 1 to 6, characterized in that, The graph distance search algorithm is the A-Star search algorithm.

8. A radar fault root cause determination device based on graph distance search, characterized in that, Including: An obtaining module for obtaining the key alarm code sequence during the fault period; A determining module for determining the causal alarm code sequence corresponding to the key alarm code sequence based on the preset alarm code path graph through the graph distance search algorithm; A calculating module for calculating the proportion of alarm codes of each fault type in the causal alarm code sequence to obtain the membership degree of each fault type, and using the fault type with the largest membership degree as the root cause type of the radar fault.

9. An electronic device, characterized in that, Including: At least one processor; And A memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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